Motion Compression using Principal Geodesics Analysis

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dc.contributor.authorTournier, M.en_US
dc.contributor.authorWu, X.en_US
dc.contributor.authorCourty, N.en_US
dc.contributor.authorArnaud, E.en_US
dc.contributor.authorReveret, L.en_US
dc.date.accessioned2015-02-23T10:15:36Z
dc.date.available2015-02-23T10:15:36Z
dc.date.issued2009en_US
dc.description.abstractDue to the growing need for large quantities of human animation data in the entertainment industry, it has become a necessity to compress motion capture sequences in order to ease their storage and transmission. We present a novel, lossy compression method for human motion data that exploits both temporal and spatial coherence. Given one motion, we first approximate the poses manifold using Principal Geodesics Analysis (PGA) in the configuration space of the skeleton. We then search this approximate manifold for poses matching end-effectors constraints using an iterative minimization algorithm that allows for real-time, data-driven inverse kinematics. The compression is achieved by only storing the approximate manifold parametrization along with the end-effectors and root joint trajectories, also compressed, in the output data. We recover poses using the IK algorithm given the end-effectors trajectories. Our experimental results show that considerable compression rates can be obtained using our method, with few reconstruction and perceptual errors.en_US
dc.description.number2en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume28en_US
dc.identifier.doi10.1111/j.1467-8659.2009.01375.xen_US
dc.identifier.issn1467-8659en_US
dc.identifier.pages355-364en_US
dc.identifier.urihttps://doi.org/10.1111/j.1467-8659.2009.01375.xen_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltden_US
dc.titleMotion Compression using Principal Geodesics Analysisen_US
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